Moral competence in AI: alignment, fairness and human rights | IASEAI '26

How should we evaluate moral reasoning in AI systems—and what does it mean for machines to exhibit genuine moral competence? This breakout session from IASEAI '26 explores how AI systems engage with human values, moral reasoning, and ethical decision-making. From assessing moral competence in language models to understanding how humans attribute responsibility in AI-driven outcomes, speakers examine both the technical and philosophical challenges of aligning AI systems with human norms. Across two segments, the session highlights emerging approaches to evaluating moral reasoning, pluralism, and alignment—alongside the implications for governance, accountability, and real-world deployment. Daniel Kilov — Discerning What Matters: A Multi-Dimensional Assessment of Moral Competence in LLMs María Victoria Caro — Human Attribution of Causality to AI Across Agency, Misuse, and Misalignment Rashid Mushkani — Measuring What Matters: The AI Pluralism Index Anita Keshmirian — Many LLMs Are More Utilitarian Than One Kevin Baum — Breaking Up with Normatively Monolithic Agency with GRACE: A Reason-Based Neuro-Symbolic Architecture for Safe and Ethical AI Alignment Sydney Levine — Resource Rational Contractualism Should Guide AI Alignment 📍 Recorded at UNESCO Headquarters, Paris The International Association for Safe and Ethical AI (IASEAI) is a global professional association bringing together researchers, policymakers, and practitioners working to ensure that advanced AI systems operate safely and ethically for the benefit of humanity. Learn more: https://www.iaseai.org #AI #AISafety #AIGovernance #AIpolicy #IASEAI #ArtificialIntelligence #ResponsibleAI